• DocumentCode
    2636519
  • Title

    Parallel imaging: some signal processing issues and solutions

  • Author

    Liang, Zhi-Pei ; Ying, Lei ; Xu, Dan ; Yuan, Lei

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Illinois Univ., Champaign, IL, USA
  • fYear
    2004
  • fDate
    15-18 April 2004
  • Firstpage
    1204
  • Abstract
    Parallel imaging using multiple receiver coils has emerged as an effective tool to reduce imaging time in various MRI applications. Mathematically, the imaging equation can be expressed as a weighted Fourier transform, and the image reconstruction formula can be derived from Papoulis´ generalized sampling theorem. Although perfect reconstructions can be obtained under ideal conditions, several signal processing problems exist in practical settings. This paper discusses some of these problems. Specifically, it analyzes the effect of data truncation, addresses the problem of estimating the coil sensitivity functions, and proposes a regularization scheme to cope with the ill-conditioned inverse problem associated with achieving high acceleration factors.
  • Keywords
    Fourier transforms; biomedical MRI; coils; image reconstruction; image sampling; inverse problems; medical image processing; MRI; Papoulis generalized sampling theorem; acceleration factors; coil sensitivity function estimation; data truncation effect; ill-conditioned inverse problem; image reconstruction formula; imaging equation; imaging time reduction; multiple receiver coils; parallel imaging; regularization scheme; signal processing; weighted Fourier transform; Acceleration; Coils; Equations; Fourier transforms; Image reconstruction; Image sampling; Inverse problems; Magnetic resonance imaging; Signal processing; Signal sampling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging: Nano to Macro, 2004. IEEE International Symposium on
  • Print_ISBN
    0-7803-8388-5
  • Type

    conf

  • DOI
    10.1109/ISBI.2004.1398760
  • Filename
    1398760